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Abstract

Using an extensive database of in situ observations we present a model that estimates the particle backscattering coefficient as a function of the total chlorophyll concentration in the open-ocean (Case-1 waters). The parameters of the model include a constant background component and the chlorophyll-specific backscattering coefficients associated with small (<20μm) and large (>20μm) phytoplankton. The new model performed with similar accuracy when compared with a traditional power-law function, with the additional benefit of providing information on the role of phytoplankton size. The observed spectral-dependency (γ) of model parameters was consistent with past observations, such that γ associated with the small phytoplankton population was higher than that of large phytoplankton. Furthermore, γ associated with the constant background component suggests this component is likely attributed to submicron particles. We envisage that the model would be useful for improving Case-1 ocean-colour models, assimilating light into multi-phytoplankton ecosystem models and improving estimates of phytoplankton size structure from remote sensing.

A. Morel and Y-H. Ahn, “Optics of heterotrophic nanoflagellates and ciliates: A tentative assessment of their scattering role in oceanic waters compared to those of bacterial and algal cells,” J. Mar. Res. 49, 177–202 (1991).
[Crossref]

1992 (1)

1991 (3)

A. Morel and Y-H. Ahn, “Optics of heterotrophic nanoflagellates and ciliates: A tentative assessment of their scattering role in oceanic waters compared to those of bacterial and algal cells,” J. Mar. Res. 49, 177–202 (1991).
[Crossref]

Ahn, Y-H.

A. Morel and Y-H. Ahn, “Optics of heterotrophic nanoflagellates and ciliates: A tentative assessment of their scattering role in oceanic waters compared to those of bacterial and algal cells,” J. Mar. Res. 49, 177–202 (1991).
[Crossref]

A. Morel and Y-H. Ahn, “Optics of heterotrophic nanoflagellates and ciliates: A tentative assessment of their scattering role in oceanic waters compared to those of bacterial and algal cells,” J. Mar. Res. 49, 177–202 (1991).
[Crossref]

J. Mar. Res. (1)

A. Morel and Y-H. Ahn, “Optics of heterotrophic nanoflagellates and ciliates: A tentative assessment of their scattering role in oceanic waters compared to those of bacterial and algal cells,” J. Mar. Res. 49, 177–202 (1991).
[Crossref]

Figures (7)

The geographic distribution of the bbp(λ) and chlorophyll data used in this study. Light grey pixels represent cloud or high sun-zenith angles for the May 2006 SeaWiFS composite and dark grey pixels represent Case-2 waters as classified according to Lee and Hu [2].

The particle backscattering coefficient (bbp) as a function of the chlorophyll concentration (C) for samples in database A and B. Database A is plotted at 470 nm (a) and 526 nm (b), with models parameterised to database A superimposed. Database B is plotted at 470 nm (c) and 526 nm (d) with models parameterised to the database A superimposed.

The pigment model of Brewin et al. [38] (parameters recomputed from [28], see Table 1) plotted alongside size-specific fractional contributions to total chlorophyll estimated from independent HPLC data (576 samples) used in this study [36, 38, 64]. F1, F2 and F3 denote the fractions of pico-, nano- and micro-phytoplankton in total chlorophyll. Note that for the fractions, δ and Δ are provided in linear space and all HPLC samples in cruises other than NOMAD are taken from the top 10 m of the water column. NOMAD samples are from version 2.0 in Case-1 waters [2] and all coincident data in NOMAD Version 1.3.h (used for the parameterisation of Eq. (8) and (9)) were removed.

The particle backscattering coefficient (bbp) as a function of the chlorophyll concentration (C) for samples in database C (satellite data). Models of Sathyendranath et al. [16] and Huot et al. [24] are also shown in (b) and (d) for comparison.

(a) and (b) show the spectral dependency in model parameters (Eq. (21)) for database A and D. (c) shows the fractional contribution of each component population to bbp(470) for a given chlorophyll concentration estimated using Eq. (22) for both database A and D, coloured shading represents a model ensemble calculated by varying model parameters between 95% confidence intervals (Table 3), in every possible permutation. (d) shows estimated γ using Eq. (21) as a function of chlorophyll, as well as the minimum and maximum of the model ensemble.

# Note that S1 and S1,2 can simply be derived by rearrangement. The product of
S1×C1m and
S1,2×C1,2m is instead provided, as it represents the derivative of Eq. (8) and (9) with respect to total chlorophyll at its origin. This product should never exceed one as it would imply larger size-fractionated chlorophyll than total chlorophyll.$ 95% confidence intervals are in brackets and were estimated using a Monte-Carlo approach.* Denotes model fit using
C1,2m and S1,2 derived from re-fitting the three-component model of Brewin et al. [38] to pigment data in Brewin et al. [28], but using the fucoaxanthin adjustment of Devred et al. [31].

Table 2

Results from the statistical tests between models and database A, B and C. All statistical tests were performed in log10 space.

# Note that S1 and S1,2 can simply be derived by rearrangement. The product of
S1×C1m and
S1,2×C1,2m is instead provided, as it represents the derivative of Eq. (8) and (9) with respect to total chlorophyll at its origin. This product should never exceed one as it would imply larger size-fractionated chlorophyll than total chlorophyll.$ 95% confidence intervals are in brackets and were estimated using a Monte-Carlo approach.* Denotes model fit using
C1,2m and S1,2 derived from re-fitting the three-component model of Brewin et al. [38] to pigment data in Brewin et al. [28], but using the fucoaxanthin adjustment of Devred et al. [31].

Table 2

Results from the statistical tests between models and database A, B and C. All statistical tests were performed in log10 space.